Protocol analysis data collection technique implemented for artificial intelligence design

Rodgers, Waymond; Al-Shaikh, Sinan; Khalil, Mohamed

Abstract

This article suggests that artificial intelligence (AI) can automate protocol analysis, a form of data analysis in cognitive psychology for inferring the information processes used by individuals from their verbal behavior while solving a problem. We propose a framework to employ think-aloud protocols (TaP) and thematic analysis in qualitative accounting research. Specifically, we use the TaP methodology to explore the impact of legal conflict and the lack of international financial reporting standards (IFRS) knowledge on implementing these accounting standards in a developing country (i.e., Iraq). The article analyzes 32 semi-structured in-depth phone interviews with external auditors, preparers, the capital market, national professional accounting and auditing associations, and academics. The results indicate that the lack of an AI framework, IFRS knowledge, and legislation conflict may adversely interact with standard implementation. This article explores how protocol analysis can benefit from AI support and provide design features. Protocol analysis can provide opportunities for future article, design, and action.

Citation

Rodgers, W., Al-Shaikh, S., & Khalil, M. (in press). Protocol analysis data collection technique implemented for artificial intelligence design. IEEE Transactions on Engineering Management, https://doi.org/10.1109/TEM.2023.3269291

• Journal Article Type: Article
• Acceptance Date: Apr 19, 2023
• Online Publication Date: May 9, 2023
• Deposit Date: May 10, 2023
• Publicly Available Date: May 30, 2023
• Journal: IEEE Transactions on Engineering Management
• Print ISSN: 0018-9391
• Electronic ISSN: 1558-0040
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1109/TEM.2023.3269291
• Keywords: Artificial intelligence; Protocols; Task analysis; Standards; Psychology; Cognitive processes; Problem-solving
• Public URL: https://hull-repository.worktribe.com/output/4288267